---
title: "Statistics"
output:
flexdashboard::flex_dashboard:
orientation: columns
social: menu
source_code: embed
---
```{r setup, include=FALSE}
# rm(list=ls())
library(flexdashboard)
library(ggplot2)
library(plotly)
library(tidyr)
library(readxl)
library(leaflet)
library(stringr)
library(DT)
cob_sub_merge <- read.csv("Country of birth of people aged 15-24 by Suburb.csv",stringsAsFactors = F)
#VPHS data
psy_dist <- read.csv("Level of psychological distress 2015-19.csv",stringsAsFactors = F)
diag_anxdep <- read.csv("Ever diagnosed with anxiety or depression 2015-19.csv",stringsAsFactors = F)
```
Column {.tabset .tabset-fade}
-----------------------------------------------------------------------
### **Level of Psychological distress**
```{r Level of Psychological distress, echo=FALSE}
# Level of Psychological distress
psy_dist_graph <- psy_dist %>%
gather(key,value,-Year) %>%
mutate(value=as.integer(value))
psy_dist_graph$key <- factor(psy_dist_graph$key,levels=c('Low','Moderate','High','Very_High', 'High_or_Very_High'))
sizes <- c('Low' = 1, 'Moderate' = 1, 'High' = 1, 'Very_High' = 1, 'High_or_Very_High' = 1)
lpd <- ggplot(psy_dist_graph,aes(x=Year,y=value,group=key,color=key))+
geom_point()+
labs(title =str_wrap('Changes in the level of psychological distress for Victorian adults over the years'),
subtitle = str_wrap("The line chart visualizes the proportion (%) of adult population (18+ years), by level of psychological distress changes in Victoria over 2015-2019. The higher level of psychological distress for was the highest in 2019."),
caption = "•Data obtained from Victorian Population Health Survey",
x='',
y='Number of people') +
geom_line(aes(colour = key, size = key, group = key)) +
scale_size_manual(values = sizes) +
scale_color_manual(values = c(rcartocolor::carto_pal(name = "Bold"), "grey50"))+
theme_bw()
lpd
```
### **Diagnosed with anxiety/depression**
```{r Diagnosed with anxiety/depression, echo=FALSE}
names(diag_anxdep) <- c("Year","Proportion_of_people")
diag_ad_graph <-ggplot(diag_anxdep,aes(x=Year,y=Proportion_of_people))+
geom_line(size=1,color="#0174DF")+
geom_point(size=4,shape=21,fill="white") +
labs(title =str_wrap('Proportion of adults that were diagnosed with anxiety or depression over time'),
subtitle = str_wrap("The line chart visualizes the proportion (%) of adult population (18+ years), with anxiety or depression in Victoria over 2015-2019. The proportion of adults has been gradually increasing over the years."),
caption = "•Data obtained from Victorian Population Health Survey",
x="",
y="Proportion of people")+
theme_bw()
diag_ad_graph
```
=======
---
title: "Statistics"
output:
flexdashboard::flex_dashboard:
orientation: columns
social: menu
source_code: embed
---
```{r setup, include=FALSE}
# rm(list=ls())
library(flexdashboard)
library(ggplot2)
library(plotly)
library(tidyr)
library(readxl)
library(leaflet)
library(stringr)
library(DT)
cob_sub_merge <- read.csv("Country of birth of people aged 15-24 by Suburb.csv",stringsAsFactors = F)
#VPHS data
psy_dist <- read.csv("Level of psychological distress 2015-19.csv",stringsAsFactors = F)
diag_anxdep <- read.csv("Ever diagnosed with anxiety or depression 2015-19.csv",stringsAsFactors = F)
```
Column {.tabset .tabset-fade}
-----------------------------------------------------------------------
### **Level of Psychological distress**
```{r Level of Psychological distress, echo=FALSE}
# Level of Psychological distress
psy_dist_graph <- psy_dist %>%
gather(key,value,-Year) %>%
mutate(value=as.integer(value))
psy_dist_graph$key <- factor(psy_dist_graph$key,levels=c('Low','Moderate','High','Very_High', 'High_or_Very_High'))
sizes <- c('Low' = 1, 'Moderate' = 1, 'High' = 1, 'Very_High' = 1, 'High_or_Very_High' = 1)
lpd <- ggplot(psy_dist_graph,aes(x=Year,y=value,group=key,color=key))+
geom_point()+
labs(title =str_wrap('Changes in the level of psychological distress for Victorian adults over the years'),
subtitle = str_wrap("The line chart visualizes the proportion (%) of adult population (18+ years), by level of psychological distress changes in Victoria over 2015-2019. The higher level of psychological distress for was the highest in 2019."),
caption = "•Data obtained from Victorian Population Health Survey",
x='',
y='Number of people') +
geom_line(aes(colour = key, size = key, group = key)) +
scale_size_manual(values = sizes) +
scale_color_manual(values = c(rcartocolor::carto_pal(name = "Bold"), "grey50"))+
theme_bw()
lpd
```
### **Diagnosed with anxiety/depression**
```{r Diagnosed with anxiety/depression, echo=FALSE}
names(diag_anxdep) <- c("Year","Proportion_of_people")
diag_ad_graph <-ggplot(diag_anxdep,aes(x=Year,y=Proportion_of_people))+
geom_line(size=1,color="#0174DF")+
geom_point(size=4,shape=21,fill="white") +
labs(title =str_wrap('Proportion of adults that were diagnosed with anxiety or depression over time'),
subtitle = str_wrap("The line chart visualizes the proportion (%) of adult population (18+ years), with anxiety or depression in Victoria over 2015-2019. The proportion of adults has been gradually increasing over the years."),
caption = "•Data obtained from Victorian Population Health Survey",
x="",
y="Proportion of people")+
theme_bw()
diag_ad_graph
```
>>>>>>> b27a3970c996c92109ebc5ce9cde2ef431b91de8